Latitudes: 5 colleges lose Chinese flagship programs because of Defense Dept cuts chronicle.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from chronicle.com Daily Mail and Mail on Sunday newspapers.
A recent analysis of Twitter activity between March and August 2020 showed strong support for face coverings to reduce exposure to COVID-19, but feedback from journal reviewers led researchers to dive deeper into their data.
When the study was completed, they also unveiled that anti-mask sentiment on popular social media sites was associated with media stories on the polarized rhetoric of people, including that of former President Donald Trump and other conservative politicians, who opposed face coverings.
The study, which blended linguistics with data from political science and news media, appears in the journal
The data include 149,110 Twitter posts involving 35 distinct types of hashtags, 26 of which were associated with mask supporters. Of the total posts, 138,796 users tweeted pro-mask hashtags and 7,771 posted anti-mask hashtags. Much of the language was polarized, angry, and emotionally loaded.
E-Mail
EUGENE, Ore. April 29, 2021 An analysis of Twitter activity between March 1 and Aug. 1, 2020, found strong support by U.S. users for wearing face coverings and that a media focus on anti-mask opinions fueled the rhetoric of those opposed, report University of Oregon researchers.
The study, published April 28 in the journal
PLOS ONE, initially focused on linguistics, zeroing in on the language associated with hashtags during the study period, which began a month before the Centers for Disease Control and Prevention recommended mask-wearing to protect against COVID-19 infection.
However, to better understand that semantics, which were found to be polarized, angry and emotionally loaded, the research team had to take an interdisciplinary journey into politics and media, said Zhuo Jing-Schmidt, a professor and linguist in the UO s Department of East Asian Languages and Literatures.